Abstract: This study aims to assess the capability of the Environment and Disaster Reduction Small Satellites (HJ-CCD) images in monitoring of rice leaf area index (LAI) in terms of comparing it with the widely used Landsat-5 TM images, which has the similar spatial resolution and band wavelength ranges. On July 13th, 2009, a field investigation was conducted which exactly corresponded with the acquiring timing of a scene of TM image and a scene of HJ-CCD. The consistency of performance was evaluated in terms of the correlation of raw band reflectance, the accuracy of reversion model as well as the spatial distribution pattern of predicted LAI. From the results, a high level of correlation can be observed for raw band reflectance. The predicted accuracies of reversion models in both forms of single variable model and multi-variable model were rather approaching for HJ-CCD and TM images, which thus yielded a highly uniform spatial distribution and data distributed pattern of predicted rice LAI. Therefore, the conclusion may be safely drawn that the HJ-CCD image is feasible and suitable for rice LAI monitoring. Meanwhile, it should be noted that a certain degree of discrepancy was also existed in the model form as well as the data range of predicted rice LAI. For that reason, it is suggested that the reversion model of rice LAI should be built and applied specifically in the light of a certain type of image. In general, this study provides some important evidences that the indigenous remotely sensed data which owned the advantages as the higher revisit frequency and wider scene swath are able to satisfy several monitoring and assessing tasks in the field of agriculture.